Learning Personalisation Approach Based on Resource Description Framework
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| Publicado en: | European Conference on e-Learning (Oct 2016), p. 323-330 |
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| Autor principal: | |
| Otros Autores: | , |
| Publicado: |
Academic Conferences International Limited
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| Resumen: | The paper is aimed to analyse the problem of learning personalisation applying Resource Description Framework (RDF) standard model. Research results are two-fold: first, the results of systematic literature review on RDF application in learning are presented, and, second, RDF-based learning personalisation approach is proposed. First of all, systematic literature review was conducted in Thomson Reuters Web of Science database and using Semantic Scholar search tool. The review has shown that RDF data model is based upon the idea of making statements about web resources in the form of subject-predicate-object expressions. These expressions are known as triples in RDF terminology. The subject denotes the resource, and the predicate denotes traits or aspects of the resource and expresses a relationship between the subject and the object. The review revealed that linked data and triples-based RDF standard model could be successfully used in education. On the other hand, although linked data approach and RDF standard model are already well-known in scientific literature, only few authors have analysed its application to personalise learning process, but many authors agree that linked data and RDF-based learning personalisation trends should be further analysed. Original RDF-based learning personalisation approach is also presented in the paper. According to this approach, RDF-based personalisation of learning should be based on applying students' learning styles and intelligent technologies. The main advantages of this approach are analyses of interconnections between students' learning styles and suitable learning components (i.e. learning resources, learning methods and activities, learning tools and technologies etc.) based on using pedagogically sound vocabularies of learning components, experts' collective intelligence, and intelligent technologies (e.g. expert evaluation, ontologies, recommender systems, software agents etc.). This pedagogically sound RDF-based personalisation approach is aimed at improving learning quality and effectiveness. |
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| ISSN: | 2048-8637 2048-8645 |
| Fuente: | Education Database |